Solutions Engineer - Cloud & DevOps

About dave.io Dave.io is an AI-native cloud infrastructure service that gets infrastructure work done end to end. We believe the next evolution of cloud infrastructure is moving from AI tools that help engineers do the work to AI-native services that take ownership of it. Dave plans, executes, and manages infrastructure work end to end—delivering outcomes, not just assistance. But real infrastructure demands real accountability. Dave combines AI-native automation with a team of expert cloud engineers who stay in the loop, reviewing and approving every step and bringing the oversight, context, and human judgment needed to operate infrastructure with confidence. The result: teams can dramatically increase their infrastructure output without scaling their headcount. We’re a well-funded, seed-stage startup, and dozens of organizations already run Dave in production. Our team comes from monday.com and JFrog, and we’re building alongside the broader cloud ecosystem, with partners including AWS, GCP, Azure, compliance platforms, and leading MSPs. We’re moving fast, and we’re just getting started. The Role As a Solutions Engineer at Dave, you’ll work at the intersection of DevOps, cloud infrastructure, AI, and our customers. You’ll work directly with engineering, DevOps, and platform teams to understand their infrastructure, identify where Dave can have the biggest impact, and make sure Dave successfully operates in their production environments. This is not a traditional pre-sales Solutions Engineer role. You’ll be hands-on with real infrastructure and real customer environments - onboarding customers, connecting their stack, solving DevOps challenges, and working alongside Dave to get infrastructure work done. You’ll own the technical customer journey from initial discovery and onboarding through production and expansion, while bringing everything you learn back to our Product and Engineering teams. Responsibilities Work directly with engineering, DevOps, Platform, and Infrastructure teams to understand their environments, workflows, and challenges. Lead technical onboarding and deployment of Dave into customer environments. Work hands-on across AWS, GCP, Azure, Kubernetes, Terraform/IaC, CI/CD, observability, security, and other infrastructure tooling. Identify high-impact infrastructure work that Dave can take on - from cloud cost optimization and security fixes to provisioning, migrations, and ongoing operations. Troubleshoot complex infrastructure and integration challenges in real production environments. Work alongside Dave and our engineering team to make sure tasks are completed safely and successfully. Help customers adopt AI for infrastructure while maintaining visibility, governance, and control. Build trusted relationships with engineers, infrastructure leaders, and R&D leadership. Partner closely with Product and Engineering to turn customer needs and learnings into product improvements. Turn lessons from individual deployments into reusable playbooks, integrations, and best practices. Skills & Experience 4+ years of experience in DevOps, Cloud Engineering, SRE, Platform Engineering, Solutions Engineering, or a similar technical role. Strong hands-on experience with AWS, GCP, and/or Azure. Deep understanding of modern cloud infrastructure and production environments. Experience with Kubernetes, Terraform/IaC, CI/CD, containers, monitoring, and observability. Strong troubleshooting skills and the ability to quickly understand unfamiliar infrastructure. Comfortable working directly with customers and becoming a trusted technical partner to their engineering teams. Ability to turn loosely defined infrastructure problems into practical solutions and get them implemented. Strong customer facing communication skills and a high level of ownership. Comfortable with startup speed, ambiguity, and rapid change. Excited about AI and the opportunity to redefine how infrastructure work gets done. Experience in a customer-facing technical role such as Solutions Engineering, Forward Deployed Engineering, Technical Consulting, or Professional Services. Experience with AI agents or AI-powered developer/infrastructure tools. Deep expertise in areas such as cloud security, FinOps, Kubernetes, or infrastructure automation. Experience operating complex enterprise cloud environments. Great to have experience in an early-stage or fast-growing startup.